Does Fibromyalgia Affect the Outcomes of Spinal Cord Stimulation: An 11-Year, Multicenter, Retrospective Matched Cohort Study

Automated characterization and detection of fibromyalgia using slow wave sleep EEG signals with glucose pattern and D'hondt pooling technique

Fibromyalgia is a soft tissue rheumatism with significant qualitative and quantitative impact on sleep macro and micro architecture. The primary objective of this study is to analyze and identify automatically healthy individuals and those with fibromyalgia using sleep electroencephalography (EEG) signals. The study focused on the automatic detection and interpretation of EEG signals obtained from fibromyalgia patients. In this work, the sleep EEG signals are divided into 15-s and a total of 5358 (3411 healthy control and 1947 fibromyalgia) EEG segments are obtained from 16 fibromyalgia and 16 normal subjects. Our developed model has advanced multilevel feature extraction architecture and hence, we used a new feature extractor called GluPat, inspired by the glucose chemical, with a new pooling approach inspired by the D'hondt selection system. Furthermore, our proposed method incorporated feature selection techniques using iterative neighborhood component analysis and iterative Chi2 methods. These selection mechanisms enabled the identification of discriminative features for accurate classification. In the classification phase, we employed a support vector machine and k-nearest neighbor algorithms to classify the EEG signals with leave-one-record-out (LORO) and tenfold cross-validation (CV) techniques. All results are calculated channel-wise and iterative majority voting is used to obtain generalized results. The best results were determined using the greedy algorithm. The developed model achieved a detection accuracy of 100% and 91.83% with a tenfold and LORO CV strategies, respectively using sleep stage (2 + 3) EEG signals. Our generated model is simple and has linear time complexity.

Incidence of Lead Migration With Loss of Efficacy or Paresthesia Coverage After Spinal Cord Stimulator Implantation: Systematic Review and Proportional Meta-Analysis of Prospective Studies and Randomized Clinical Trials

OBJECTIVE

The objective of this meta-analysis was to approximate the incidence of overall lead migration, clinically significant lead migration, and asymptomatic lead migration in patients who have undergone spinal cord stimulator implantation.

MATERIALS AND METHODS

A comprehensive literature search was performed for studies published before May 31, 2022. Only randomized controlled trials and prospective observational studies with more than ten patients were included. Two reviewers analyzed the articles from the literature search for final inclusion, after which, study characteristics and outcome data were extracted. The primary dichotomous categorical outcome variables were the incidence of overall lead migration, clinically significant lead migration (defined as lead migration resulting in loss of efficacy), and asymptomatic lead migration (defined as lead migration discovered incidentally on follow-up imaging) in patients with spinal cord stimulator implant. Freeman-Tukey arcsine square root transformation for meta-analysis of proportions using random effects (DerSimonian and Laird method) was used to calculate incidence rates for the outcome variables. Pooled incidence rates and 95% CIs were calculated for the outcome variables.

RESULTS

Fifty-three studies met the inclusion criteria, with a total of 2932 patients having received spinal cord stimulator implants. The pooled incidence of overall lead migration was 9.97% (95% CI of 7.62%-12.59%). Only 24 of the included studies commented on the clinical significance of reported lead migrations, of which every lead migration was clinically significant. In these 24 studies, 96% of the reported lead migrations required a revision procedure or explant. Unfortunately, no studies that reported lead migration commented on asymptomatic lead migrations; therefore, the incidence of asymptomatic lead migrations could not be defined.

CONCLUSIONS

This meta-analysis found that the rate of lead migration in patients who have received spinal cord stimulator implants is approximately one in ten patients. This likely closely approximates the incidence of clinically significant lead migration owing to the included studies not routinely performing follow-up imaging. Therefore, lead migrations were primarily discovered owing to loss of efficacy, and no included studies clearly reported asymptomatic lead migration. The results of this meta-analysis can be used to inform patients more accurately on the risks and benefits of spinal cord stimulator implantation.

Neuromodulation Therapy for Chemotherapy-Induced Peripheral Neuropathy: A Systematic Review

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating and painful condition in patients who have received chemotherapy. The role of neuromodulation therapy in treating pain and improving neurological function in CIPN remains unclear and warrants evidence appraisal. In compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we performed a systematic review to assess change in pain intensity and neurological function after implementation of any neuromodulation intervention for CIPN. Neuromodulation interventions consisted of dorsal column spinal cord stimulation (SCS), dorsal root ganglion stimulation (DRG-S), or peripheral nerve stimulation (PNS). In total, 15 studies utilized SCS (16 participants), 7 studies utilized DRG-S (7 participants), and 1 study utilized PNS (50 participants). Per the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria, there was very low-quality GRADE evidence supporting that dorsal column SCS, DRG-S, and PNS are associated with a reduction in pain severity from CIPN. Results on changes in neurological function remained equivocal due to mixed study findings on thermal sensory thresholds and touch sensation or discrimination. Future prospective, well-powered, and comparative studies assessing neuromodulation for CIPN are warranted.

Dorsal Root Ganglion Stimulation for Lower Extremity Neuropathic Pain Syndromes: An Evidence-Based Literature Review

Dorsal root ganglion stimulation (DRG-S) is a form of selective neuromodulation therapy that targets the dorsal root ganglion. DRG-S offers analgesia in a variety of chronic pain conditions and is approved for treatment of complex regional pain syndrome (CRPS) by the US Food and Drug Administration (FDA). There has been increasing utilization of DRG-S to treat various neuropathic pain syndromes of the lower extremity, although evidence remains limited to one randomized controlled trial and 39 observational studies. In this review, we appraised the current evidence for DRG-S in the treatment of lower extremity neuropathic pain using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. The primary outcome was change in pain intensity after DRG-S compared to baseline. We stratified presentation of results based of type of neuropathy (CRPS, painful diabetic neuropathy, mononeuropathy, polyneuropathy) as well as location of neuropathy (hip, knee, foot). Future powered randomized controlled trials with homogeneous participants are warranted.